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Azure ML: Most user friendly and the cheapest!I was the president of an MBA class that used Azure ML to run analytics models. The tool was used by 40 students. We analyzed a few datasets to understand the tools, and afterward, we were able to create a few analytics products based on Azure ML.,User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared! Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch! Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free. Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there! Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.,Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not Tableau interface: last time I checked there was no easy way to connect with Tableau. Cloud based: You always need a good internet connection to use it.,10,Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster; Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat. Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details,Tableau Desktop, RStudio, KNIME Analytics Platform and Adobe Analytics,Microsoft Power BI, RStudio, Adobe Analytics, KNIME Analytics Platform, JMP Statistical Discovery Software from SAS, Oracle Business Intelligence Cloud Service
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Microsoft Azure Machine Learning Workbench
8 Ratings
Score 7.9 out of 101
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Microsoft Azure Machine Learning Workbench Reviews

Microsoft Azure Machine Learning Workbench
8 Ratings
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Score 7.9 out of 101
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Gabriel Chiararia profile photo
May 21, 2018

Microsoft Azure Machine Learning Workbench Review: "Azure ML: Most user friendly and the cheapest!"

Score 10 out of 10
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I was the president of an MBA class that used Azure ML to run analytics models. The tool was used by 40 students. We analyzed a few datasets to understand the tools, and afterward, we were able to create a few analytics products based on Azure ML.
  • User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
  • Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
  • Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
  • Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
  • Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.
  • Few models: Even though it has a lot of Machine Learning models, it is quite limited when compared to R. Most Data Scientists still use and prefer R, so the newest models tend to release as R libraries. With Azure ML, we need to wait for Microsoft to evaluate and decide if including a new model is a good idea or not
  • Tableau interface: last time I checked there was no easy way to connect with Tableau.
  • Cloud based: You always need a good internet connection to use it.
Well suited:
- Run a machine learning model the fastest and easiest way;
- Working with an organization with no coding background;
- Trying to get the most of data the cheapest and easiest way possible;
- Introducing analytics and machine learning concepts to an organization or class;

Less appropriate:
- Running complex Machine Learning models;
- Visualizing data more deeply;
- Running new analytics models;
- Running heavy statistical models;
Read Gabriel Chiararia's full review

Microsoft Azure Machine Learning Workbench Scorecard Summary

About Microsoft Azure Machine Learning Workbench

Microsoft Azure Machine Learning Workbench is and end-to-end data science and analytics solution that helps professional data scientists to prepare data, develop experiments, and deploy models in the cloud.
Categories:  Machine Learning

Microsoft Azure Machine Learning Workbench Technical Details

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